An innovative classification system for ranking the biological effects of marine aromatic hydrocarbons based on fish embryotoxicity
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Abstract: Petroleum hydrocarbon pollution is a global concern, particularly in coastal environments. Polycyclic aromatic hydrocarbons (PAHs) are regarded as the most toxic components of petroleum hydrocarbons. In this study, the biomonitoring and ranking effects of petroleum hydrocarbons and PAHs on the marine fish model Oryzias melastigma embryos were determined in the Jiulong River Estuary (JRE) and its adjacent waters in China. The results showed that the levels of petroleum hydrocarbons from almost all sites met the primary standard for marine seawater quality, and the concentrations of the 16 priority PAHs in the surface seawater were lower compared with those in other coastal areas worldwide. A new fish expert system based on the embryotoxicity of O. melastigma (OME-FES) was developed and applied in the field to evaluate the biological effects of petroleum hydrocarbons and PAHs. The selected physiological index and molecular indicators in OME-FES were appropriate biomarkers for indicating the harmful effects of petroleum hydrocarbons and PAHs. The outcome of OME-FES revealed that the biological effect levels of the sampling sites ranged from level Ⅰ (no stress) to level Ⅲ (medium stress), which is further corroborated by the findings of nested analysis of variance (ANOVA) models. Our results suggest that the OME-FES is an effective tool for evaluating and ranking the biological effects of marine petroleum hydrocarbons and PAHs. This method may also be applied to evaluate other marine pollutants based on its framework.
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Figure 2. Composition of PAHs according to different ring numbers in seawater from each site.
Figure 3. Relative mRNA expression levels of five target genes in the embryos treated with surface seawater samples at different sites compared with the control after 4 d exposure. Data are expressed as the mean ± standard error. Significant differences were accepted at * p < 0.05. Five biological replicates were conducted.
Figure 4. Star plot and IBRv2 values at each sampling site. The order of each site was arranged according to the IBRv2 values, which was decreased from left-to-right and top-to-bottom.
Table 1. Determination of the alteration level (AL)
Decreasing
parameterIncreasing and
bell-shaped parameterBiological relevance Threshold AL Threshold AL AF > 0.8 NA AF < 1.2 NA Small differences (±20%) with respect to controls; although statistically significant, they are not considered of biological relevance. AF < 0.8 − AF > 1.2 + Larger than 20%, statistically significant differences with respect to controls. The symbols “−” and “+” indicate decreased or increased physiological responses of the organisms, respectively. AF < 0.5 − − AF > 2.0 ++ Large differences (>100%) with respect to controls. The symbols “−−” and “++” indicate moderate decreased or increased physiological responses of the organisms, respectively, which are within the range of alterations induced by moderate natural stressors. Note: AF, alteration factor; NA, no alteration. 
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Table 2. Summary results of nested ANOVA analyses for IBRv2 values
Source DF SS MS F p Study areas 2 135.869 67.935 1811.151 0.000 E-T 1 93.268 93.268 4198.732 0.000 E-P 1 112.483 112.483 2134.084 0.000 T-P 1 2.273 2.273 57.537 0.000 Note: E, the estuary area; T, the tourism area; P, the port area; DF, degrees of freedom for each component; SS, the sum-of-squares; MS, the mean-squares; F and p for the hypothesis test of significant study area heterogeneity.
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Table 3. Response profiles of the biomarkers selected in OME-FES and their levels of biological organization
Biomarker Response profile Level of biological organization CYP1A1 gene increasing molecular/cellular CYP27B gene increasing molecular/cellular CYP3A40 gene increasing molecular/cellular AhR gene increasing molecular/cellular ARNT gene increasing molecular/cellular BSD score increasing tissue Survival rate decreasing organism
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Table 4. Critical values of five selected biomarkers and the threshold values of BEI
Control $\beta $ = 1.20 $\beta $ = 2.00 CYP1A1 gene 1.00 1.20 2.00 CYP27B gene 1.00 1.20 2.00 CYP3A40 gene 1.00 1.20 2.00 AhR gene 1.00 1.20 2.00 ARNT gene 1.00 1.20 2.00 Threshold values of BEI 0.00 2.54 9.65 Note: $\beta $: biomarkers and threshold values selected according to the alteration factor in Table 1 and response profiles of the molecular biomarkers in Table 3.
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Table 5. Concentrations (ng/L) of
$\Sigma $ PAHs in coastal waters from different areas worldwideSampling area Number of PAHs n Mean Min Max Reference JRE and its adjacent waters 16 12 31.0 20.22 38.71 this study Langkawi Island, Malaysia 18 − − 18.0 46.0 Zong et al., 2014 Natuna, Indonesia 17 − − 0.0 5.8 Zong et al., 2014 Oostende, Belgium 15 − − 13.0 24.0 Zong et al., 2014 Chesapeake Bay, USA 17 38 33.3 20.0 65.6 Zhou and Maskaoui, 2003 Dalian coastal area, China 9 17 60.8 50.5 74.7 Zhang et al., 2020 Maowei Sea, China 16 10 − 33.5 48.5 Zheng et al., 2022 Western Taiwan Strait, China 15 31 19.8 12.3 58.0 Wu et al., 2011 Xiamen Bay, China 16 17 17.0 7.0 26.9 Maskaoui et al., 2002 JRE, China-wet season 46 20 67.1 24.6 125.9 Wu et al., 2019 JRE, China-dry season 46 20 27.4 17.5 65.0 Wu et al., 2019 Thane creek, India 16 10 − 337 706 Tiwari et al., 2017 Persian Gulf, Iran 30 360 464 70 884 Jafarabadi et al., 2017 Aegina Island, Greece 17 − − 103 124 Zong et al., 2014 Dalian coast, China-winter 46 15 357 136 621 Hong et al., 2016 Dalian coast, China-summer 46 15 297 65 1 130 Hong et al., 2016 Luan River Estuary, China 14 9 − 231 3 664 Yan et al., 2016 Hai River Estuary, China 14 11 − 288 3 797 Yan et al., 2016 Zhangweixin River Estuary, China 15 10 − 306 7 597 Yan et al., 2016 Note: JRE: Jiulong River Estuary; n denominates the number of samples; − represents no data.
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